چکیده انگلیسی

Microcredit and small and medium enterprise (SME) finance are often pitched as alternative strategies to create employment opportunities in low-income communities. So far, though, little is known about how employment patterns compare. We integrate evidence from three surveys to show that, compared to Bangladeshi microcredit customers, typical SME employees in Bangladesh have more education and professional skills, and live in households that are notably less poor. SME jobs also require long work weeks, clashing with family responsibilities. The evidence from Bangladesh rejects the idea that SME finance more efficiently creates jobs for the population currently served by microcredit.

مقدمه انگلیسی

The original promise of microcredit was to reduce poverty by fostering self-employment in low-income communities, an idea first promoted at mass scale in Bangladesh (Yunus, 1999). But critics of Muhammad Yunus and the Bangladesh microcredit model argue that supporting larger businesses (small and medium enterprises [SMEs]) may instead create more and better jobs for poor individuals (Dichter, 2006 and Karnani, 2007). That is only possible, however, if those larger enterprises employ poor workers in large numbers. We argue that that cannot be assumed.
Most studies of SMEs implicitly or explicitly compare them to large firms (Beck & Demirgüç-Kunt, 2006). In this paper, we instead compare the employment and poverty outreach of SMEs to that of microenterprises. Because we’re interested in jobs, our focus is not on the owners of SMEs, but on their employees. If it is true that SMEs create ample jobs for poor workers, there should be a robust correlation between SME growth and poverty reduction, but little correlation is found in cross-country data (Beck, Demirgüç-Kunt, & Levine, 2005). We use micro-data from Bangladesh to explore related issues.
There are surprisingly little data on the profile of microcredit borrowers, and even less that might be matched to comparable surveys of SME employees. We draw on a series of surveys of both microcredit borrowers and SME employees, building from a 2008 survey of Bangladeshi SMEs which obtain loans from BRAC Bank, a for-profit arm of Bangladesh’s largest Nongovernmental organization (NGO). In focusing on BRAC Bank, we narrow attention to SMEs that are most likely to align with Bangladesh Rural Advancement Committee (BRAC)’s broader imperatives of development, social welfare improvement, and poverty reduction.
The “micro is too small” view rests on the assertion that supporting larger businesses might be a more efficient way to achieve similar ends to microcredit. We show that the proposition is only half right in our data from Bangladesh. SME finance at BRAC Bank is more profitable than microcredit lending in Bangladesh, and can create larger financial multipliers than investing in microcredit institutions. But we do not find that patterns of job creation (and, by implication, the distribution of social benefits) will be similar.
The data show that the average employee of a small enterprise in our sample is a 26 year old male with almost 5 years of formal education and who is semi-skilled. In contrast, Bangladeshi microcredit borrowers are mostly women, about half have no formal education and most have few professional skills. Analysis of the average likelihood that employees live in poor households shows a similar bifurcation.
Bangladesh’s labor market is atypical in the extent to which women do not participate in the formal labor market. Microcredit, which funds home-based production, was successful in Bangladesh precisely because it offered a way to serve women without requiring them to enter the formal labor market. In line with this, we find that microcredit borrowers are far more likely to be female (91% vs. 7% of SME employees). This finding is hardly surprising: Microcredit was designed to serve women, and SMEs are constrained in their ability to hire women.
Our contribution is to go further to show, first, that SME employees are not typically drawn from households that are similar to those of microcredit borrowers. The BRAC survey is particularly valuable in including questions that can be used to predict the likelihood that the SME employees’ households are below global poverty lines. We then compare household-level predictions from the BRAC survey to similarly-constructed likelihood scores taken from independent data on microcredit borrowers in Bangladesh.
Second, we show that, were cultural barriers to women’s entry into labor markets to fall, microcredit borrowers would find themselves competing for SME jobs where current workers are more educated and more highly skilled. Third, even were cultural barriers to women’s entry into labor markets to fall, the nature of SME jobs would be challenging for workers carrying central family responsibilities. The data show that SME employees work long weeks (on average 11 h a day, 6 days a week).
In sum, SMEs in Bangladesh are not typically creating jobs that reach the kinds of workers supported by microcredit, nor does the evidence show that SMEs are reaching many members of the same kinds of families as microcredit customers. If these findings generalize to other labor markets, they help explain the lack of a cross-country correlation between SME growth and poverty reduction found by Beck, Demirgüç-Kunt, and Maksimovic (2005).1
The rest of the paper is organized as follows. Section 2 reviews the evidence on the role of SME finance in poverty reduction, particularly through employment. Section 3 describes our data. Section 4 presents evidence on the characteristics of SME employees and microcredit borrowers in Bangladesh, and Section 5 analyzes the characteristics of jobs offered by SMEs. Section 6 focuses on the efficiency of SME lending vs. that of microcredit. Section 7 concludes by pulling together the evidence presented in Sections 4, 5 and 6 and describing an alternative explanation.

نتیجه گیری انگلیسی

SME finance is gaining attention as a possible alternative to microcredit investment in the fight for poverty reduction, notably because SMEs provide employment on a much larger scale than microenterprises supported by microcredit. Our evidence suggests that in Bangladesh the two forms of support are complements, not substitutes.
A survey of employee of Bangladeshi SMEs shows that the typical employee is a young, educated male, whose household tends to be better off than the typical households of microcredit borrowers. Working in a small enterprise is hard: employees work 70 h per week on average, for very low hourly wages. These long hours are not particularly friendly for workers with substantial family responsibilities.
As described above, the poverty scorecard-based data indicate that employees of the SMEs in our sample are less poor, on average, than microcredit borrowers. An important question remains open about the causal impact of an increase in SMEs’ access to credit on employment and, through employment, on poverty reduction. The ideal evaluation of the marginal impact of lending to SMEs would rest on a careful counterfactual: What would have happened to the SME firms and their employees if the firms had not borrowed? Our evidence shows that SME employees live in less poor households, on average, than microcredit borrowers, but does not speak on whether SME employment is what caused households to be less poor. Our evidence is consistent with typical SME workers being drawn from different households than typical microcredit customers, and we have stressed the “selection effect.” Our data do not allow us to investigate the alternative hypothesis that typical SME employees originally came from households very similar to those of microcredit customers—but that working at the SME increased incomes so much that household-level indicators such as kitchen quality, latrine quality, television ownership, school attendance, and water source were qualitatively improved. We expect that SME employment did improve the conditions of households, but it remains to be shown that any improvements would have been so great that they can explain the wide differences we find.